Custom selected reference genes outperform pre-defined reference genes in transcriptomic analysis

Abstract Background: RNA sequencing allows the measuring of gene expression at a resolution unmet by expression arrays or RT-qPCR. It is however necessary to normalize sequencing data by library size, transcript size and composition, among other factors, before comparing expression levels. The use of internal control genes or spike-ins is advocated in the literature for scaling read counts, but the methods for choosing reference genes are mostly targeted at RT-qPCR studies and require a set of pre-selected candidate controls or pre-selected target genes. Results: Here, we report an R-based script to select internal control genes based solely on read counts and gene sizes. This novel method first normalizes the read counts to Transcripts per Million (TPM) and then excludes weakly expressed genes using the DAFT script to calculate the cut-off. It then selects as references the genes with lowest TPM covariance. We used this method to pick custom reference genes for the differential expression analysis of three transcriptome sets from transgenic Arabidopsis plants expressing heterologous fungal effector proteins tagged with GFP (using GFP alone as the control). The custom reference genes showed lower covariance and fold change as well as a broader range of expression levels than commonly used reference genes. When analyzed with NormFinder, both typical and custom reference genes were considered suitable internal controls, but the custom selected genes were more stable. geNorm produced a similar result in which most custom selected genes ranked higher (i.e. were more stable) than commonly used reference genes. Conclusions: The proposed method is innovative, rapid and simple. Since it does not depend on genome annotation, it can be used with any organism, and does not require pre-selected reference candidates or target genes that are not always available.

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Custom selected reference genes outperform pre-defined reference genes in transcriptomic analysis

10.21203/rs.2.9587/v2 ◽

2019 ◽

Author(s):

Karen Cristine Gonçalves Dos Santos ◽

Isabel Desgagné-Penix ◽

Hugo Germain

Keyword(s):

Internal Control ◽

Reference Genes ◽

Target Genes ◽

Differential Expression Analysis ◽

Effector Proteins ◽

Sequencing Data ◽

Library Size ◽

Expression Levels ◽

Expression Arrays ◽

Internal Control Genes

Abstract Background: RNA sequencing allows the measuring of gene expression at a resolution unmet by expression arrays or RT-qPCR. It is however necessary to normalize sequencing data by library size, transcript size and composition, among other factors, before comparing expression levels. The use of internal control genes or spike-ins is advocated in the literature for scaling read counts, but the methods for choosing reference genes are mostly targeted at RT-qPCR studies and require a set of pre-selected candidate controls or pre-selected target genes. Results: Here, we report an R-based script to select internal control genes based solely on read counts and gene sizes. This novel method first normalizes the read counts to Transcripts per Million (TPM) and then excludes weakly expressed genes using the DAFS script to calculate the cut-off. It then selects as references the genes with lowest TPM covariance. We used this method to pick custom reference genes for the differential expression analysis of three transcriptome sets from transgenic Arabidopsis plants expressing heterologous fungal effector proteins tagged with GFP (using GFP alone as the control). The custom reference genes showed lower covariance and fold change as well as a broader range of expression levels than commonly used reference genes. When analyzed with NormFinder, both typical and custom reference genes were considered suitable internal controls, but the expression of custom selected genes was more stable. geNorm produced a similar result in which most custom selected genes ranked higher (i.e. expression more stable) than commonly used reference genes. Conclusions: The proposed method is innovative, rapid and simple. Since it does not depend on genome annotation, it can be used with any organism, and does not require pre-selected reference candidates or target genes that are not always available.

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Custom selected reference genes outperform pre-defined reference genes in transcriptomic analysis

10.21203/rs.2.9587/v3 ◽

2019 ◽

Author(s):

Karen Cristine Gonçalves Dos Santos ◽

Isabel Desgagné-Penix ◽

Hugo Germain

Keyword(s):

Internal Control ◽

Reference Genes ◽

Target Genes ◽

Differential Expression Analysis ◽

Effector Proteins ◽

Sequencing Data ◽

Library Size ◽

Expression Levels ◽

Expression Arrays ◽

Internal Control Genes

Abstract Background : RNA sequencing allows the measuring of gene expression at a resolution unmet by expression arrays or RT-qPCR. It is however necessary to normalize sequencing data by library size, transcript size and composition, among other factors, before comparing expression levels. The use of internal control genes or spike-ins is advocated in the literature for scaling read counts, but the methods for choosing reference genes are mostly targeted at RT-qPCR studies and require a set of pre-selected candidate controls or pre-selected target genes. Results : Here, we report an R-based pipeline to select internal control genes based solely on read counts and gene sizes. This novel method first normalizes the read counts to Transcripts per Million (TPM) and then excludes weakly expressed genes using the DAFS script to calculate the cut-off. It then selects as references the genes with lowest TPM covariance. We used this method to pick custom reference genes for the differential expression analysis of three transcriptome sets from transgenic Arabidopsis plants expressing heterologous fungal effector proteins tagged with GFP (using GFP alone as the control). The custom reference genes showed lower covariance and fold change as well as a broader range of expression levels than commonly used reference genes. When analyzed with NormFinder, both typical and custom reference genes were considered suitable internal controls, but the expression of custom selected genes was more stable. geNorm produced a similar result in which most custom selected genes ranked higher ( i.e. expression more stable) than commonly used reference genes. Conclusions : The proposed method is innovative, rapid and simple. Since it does not depend on genome annotation, it can be used with any organism, and does not require pre-selected reference candidates or target genes that are not always available.

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Custom selected reference genes outperform pre-defined reference genes in transcriptomic analysis

BMC Genomics ◽

10.1186/s12864-019-6426-2 ◽

2020 ◽

Vol 21 (1) ◽

Cited By ~ 3

Author(s):

Karen Cristine Gonçalves dos Santos ◽

Isabel Desgagné-Penix ◽

Hugo Germain

Keyword(s):

Internal Control ◽

Reference Genes ◽

Target Genes ◽

Differential Expression Analysis ◽

Effector Proteins ◽

Sequencing Data ◽

Library Size ◽

Expression Levels ◽

Expression Arrays ◽

Internal Control Genes

Abstract Background RNA sequencing allows the measuring of gene expression at a resolution unmet by expression arrays or RT-qPCR. It is however necessary to normalize sequencing data by library size, transcript size and composition, among other factors, before comparing expression levels. The use of internal control genes or spike-ins is advocated in the literature for scaling read counts, but the methods for choosing reference genes are mostly targeted at RT-qPCR studies and require a set of pre-selected candidate controls or pre-selected target genes. Results Here, we report an R-based pipeline to select internal control genes based solely on read counts and gene sizes. This novel method first normalizes the read counts to Transcripts per Million (TPM) and then excludes weakly expressed genes using the DAFS script to calculate the cut-off. It then selects as references the genes with lowest TPM covariance. We used this method to pick custom reference genes for the differential expression analysis of three transcriptome sets from transgenic Arabidopsis plants expressing heterologous fungal effector proteins tagged with GFP (using GFP alone as the control). The custom reference genes showed lower covariance and fold change as well as a broader range of expression levels than commonly used reference genes. When analyzed with NormFinder, both typical and custom reference genes were considered suitable internal controls, but the custom selected genes were more stably expressed. geNorm produced a similar result in which most custom selected genes ranked higher (i.e. were more stably expressed) than commonly used reference genes. Conclusions The proposed method is innovative, rapid and simple. Since it does not depend on genome annotation, it can be used with any organism, and does not require pre-selected reference candidates or target genes that are not always available.

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Identification of reference genes for gene expression studies during seed germination and seedling establishment in Ricinus communis L.

Seed Science Research ◽

10.1017/s0960258514000294 ◽

2014 ◽

Vol 24 (4) ◽

pp. 341-352 ◽

Cited By ~ 15

Author(s):

Paulo R. Ribeiro ◽

Bas J. W. Dekkers ◽

Luzimar G. Fernandez ◽

Renato D. de Castro ◽

Wilco Ligterink ◽

...

Keyword(s):

Gene Expression ◽

Seed Germination ◽

Reference Genes ◽

Target Genes ◽

Ricinus Communis ◽

Quantitative Polymerase Chain Reaction ◽

Optimal Combination ◽

Expression Levels ◽

Gene Expression Studies ◽

Gene Expression Levels

AbstractReverse transcription-quantitative polymerase chain reaction (RT-qPCR) is an important technology to analyse gene expression levels during plant development or in response to different treatments. An important requirement to measure gene expression levels accurately is a properly validated set of reference genes. In this context, we analysed the potential use of 17 candidate reference genes across a diverse set of samples, including several tissues, different stages and environmental conditions, encompassing seed germination and seedling growth in Ricinus communis L. These genes were tested by RT-qPCR and ranked according to the stability of their expression using two different approaches: GeNorm and NormFinder. GeNorm and Normfinder indicated that ACT, POB and PP2AA1 comprise the optimal combination for normalization of gene expression data in inter-tissue (heterogeneous sample panel) studies. We also describe the optimal combination of reference genes for a subset of root, endosperm and cotyledon samples. In general, the most stable genes suggested by GeNorm are very consistent with those indicated by NormFinder, which highlights the strength of the selection of reference genes in our study. We also validated the selected reference genes by normalizing the expression levels of three target genes involved in energy metabolism with the reference genes suggested by GeNorm and NormFinder. The approach used in this study to identify stably expressed genes, and thus potential reference genes, was applied successfully for R. communis and it provides important guidelines for RT-qPCR studies in seeds and seedlings for other species (especially in those cases where extensive microarray data are not available).

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Identification of stable reference genes for lipopolysaccharide-stimulated macrophage gene expression studies

Biology Methods and Protocols ◽

10.1093/biomethods/bpw005 ◽

2016 ◽

Vol 1 (1) ◽

Cited By ~ 1

Author(s):

Roshini Kalagara ◽

Weimin Gao ◽

Honor L. Glenn ◽

Colleen Ziegler ◽

Laura Belmont ◽

...

Keyword(s):

Gene Expression ◽

Ribosomal Protein ◽

Reference Gene ◽

Reference Genes ◽

Target Genes ◽

Stable Gene ◽

Expression Levels ◽

Qrt Pcr ◽

Expression Studies ◽

Gene Expression Studies

Gene expression studies which utilize lipopolysaccharide (LPS)-stimulated macrophages to model immune signaling are widely used for elucidating the mechanisms of inflammation-related disease. When expression levels of target genes are quantified using Real-Time quantitative Reverse Transcription Polymerase Chain Reaction (qRT-PCR), they are analyzed in comparison to reference genes, which should have stable expression. Judicious selection of reference genes is, therefore, critical to interpretation of qRT-PCR results. Ideal reference genes must be identified for each experimental system and demonstrated to remain constant under the experimental conditions. In this study, we evaluated the stability of eight common reference genes: Beta-2-microglobulin (B2M), Cyclophilin A/Peptidylprolyl isomerase A, glyceraldehyde-3-phosphatedehydrogenase (GAPDH), Hypoxanthine Phosphoribosyltransferase 1, Large Ribosomal Protein P0, TATA box binding protein, Ubiquitin C (UBC), and Ribosomal protein L13A. Expression stability of each gene was tested under different conditions of LPS stimulation and compared to untreated controls. Reference gene stabilities were analyzed using Ct value comparison, NormFinder, and geNorm. We found that UBC, closely followed by B2M, is the most stable gene, while the commonly used reference gene GAPDH is the least stable. Thus, for improved accuracy in evaluating gene expression levels, we propose the use of UBC to normalize PCR data from LPS-stimulated macrophages.

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Gene Expression and Photophysiological Changes in Pocillopora acuta Coral Holobiont Following Heat Stress and Recovery

Microorganisms ◽

10.3390/microorganisms8081227 ◽

2020 ◽

Vol 8 (8) ◽

pp. 1227

Author(s):

Rosa Celia Poquita-Du ◽

Yi Le Goh ◽

Danwei Huang ◽

Loke Ming Chou ◽

Peter A. Todd

Keyword(s):

Gene Expression ◽

Heat Stress ◽

Target Genes ◽

Differential Expression Analysis ◽

Heat Exposure ◽

Small Heat Shock Protein ◽

Expression Levels ◽

Chl A ◽

Coral Holobiont ◽

Gene Expression Levels

The ability of corals to withstand changes in their surroundings is a critical survival mechanism for coping with environmental stress. While many studies have examined responses of the coral holobiont to stressful conditions, its capacity to reverse responses and recover when the stressor is removed is not well-understood. In this study, we investigated among-colony responses of Pocillopora acuta from two sites with differing distance to the mainland (Kusu (closer to the mainland) and Raffles Lighthouse (further from the mainland)) to heat stress through differential expression analysis of target genes and quantification of photophysiological metrics. We then examined how these attributes were regulated after the stressor was removed to assess the recovery potential of P. acuta. The fragments that were subjected to heat stress (2 °C above ambient levels) generally exhibited significant reduction in their endosymbiont densities, but the extent of recovery following stress removal varied depending on natal site and colony. There were minimal changes in chl a concentration and maximum quantum yield (Fv/Fm, the proportion of variable fluorescence (Fv) to maximum fluorescence (Fm)) in heat-stressed corals, suggesting that the algal endosymbionts’ Photosystem II was not severely compromised. Significant changes in gene expression levels of selected genes of interest (GOI) were observed following heat exposure and stress removal among sites and colonies, including Actin, calcium/calmodulin-dependent protein kinase type IV (Camk4), kinesin-like protein (KIF9), and small heat shock protein 16.1 (Hsp16.1). The most responsive GOIs were Actin, a major component of the cytoskeleton, and the adaptive immune-related Camk4 which both showed significant reduction following heat exposure and subsequent upregulation during the recovery phase. Our findings clearly demonstrate specific responses of P. acuta in both photophysiological attributes and gene expression levels, suggesting differential capacity of P. acuta corals to tolerate heat stress depending on the colony, so that certain colonies may be more resilient than others.

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The novel microRNAs hsa-miR-nov7 and hsa-miR-nov3 are over-expressed in locally advanced breast cancer

10.1101/831560 ◽

2019 ◽

Author(s):

Deepak Poduval ◽

Zuzana Sichmanova ◽

Anne Hege Straume ◽

Per Eystein Lønning ◽

Stian Knappskog

Keyword(s):

Breast Cancer ◽

Target Genes ◽

Locally Advanced Breast Cancer ◽

Statistical Significance ◽

Locally Advanced ◽

Advanced Breast ◽

Transcriptional Level ◽

Sequencing Data ◽

Expression Array ◽

Expression Levels

AbstractmiRNAs are an important class of small non-coding RNAs, which play a versatile role in gene regulation at the post-transcriptional level. Expression of miRNAs is often deregulated in human cancers.We analyzed small RNA massive parallel sequencing data from 50 locally advanced breast cancers aiming to identify novel breast cancer related miRNAs. We successfully predicted 10 novel miRNAs, out of which 2 (hsa-miR-nov3 and hsa-miR-nov7) were recurrent. Applying high sensitivity qPCR, we detected these two microRNAs in 206 and 214 out of 223 patients in the study from which the initial cohort of 50 samples were drawn. We found hsa-miR-nov3 and hsa-miR-nov7 both to be overexpressed in tumor versus normal breast tissue in a separate set of 13 patients (p=0.009 and p=0.016, respectively) from whom both tumor tissue and normal tissue were available. We observed hsa-miR-nov3 to be expressed at higher levels in ER-positive compared to ER-negative tumors (p=0.037). Further stratifications revealed particularly low levels in the her2-like and basal-like cancers compared to other subtypes (p=0.009 and 0.040, respectively).We predicted target genes for the 2 microRNAs and identified inversely correlated genes in mRNA expression array data available from 203 out of the 223 patients. Applying the KEGG and GO annotations to target genes revealed pathways essential to cell development, communication and homeostasis.Although a weak association between high expression levels of hsa-miR-nov7 and poor survival was observed, this did not reach statistical significance. hsa-miR-nov3 expression levels had no impact on patient survival.

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Extracellular microRNA 3’ end modification across diverse body fluids

10.1101/2020.03.24.006551 ◽

2020 ◽

Cited By ~ 1

Author(s):

Kikuye Koyano ◽

Jae Hoon Bahn ◽

Xinshu Xiao

Keyword(s):

Rna Sequencing ◽

Target Genes ◽

Small Rna Sequencing ◽

Specific Information ◽

Data Sets ◽

Sequencing Data ◽

Extracellular Rna ◽

Expression Levels ◽

Depth Analysis ◽

Extracellular Mirnas

ABSTRACTmicroRNAs (miRNAs) are small non-coding RNAs that play critical roles in gene regulation. The presence of miRNAs in extracellular biofluids is increasingly recognized. However, most previous characterization of extracellular miRNAs focused on their overall expression levels. Alternative sequence isoforms and modifications of miRNAs were rarely considered in the extracellular space. Here, we developed a highly accurate bioinformatic method, called miNTA, to identify 3’ non-templated additions (NTAs) of miRNAs using small RNA-sequencing data. Using miNTA, we conducted an in-depth analysis of miRNA 3’ NTA profiles in 1047 extracellular RNA-sequencing data sets of 4 types of biofluids. This analysis identified abundant 3’ uridylation and adenylation of miRNAs, with an estimated false discovery rate of <5%. Strikingly, we found that 3’ uridylation levels enabled segregation of different types of biofluids, more effectively than overall miRNA expression levels. This observation suggests that 3’ NTA levels possess fluid-specific information insensitive to batch effects. In addition, we observed that extracellular miRNAs with 3’ uridylations are enriched in processes related to angiogenesis, apoptosis and inflammatory response, and this type of modification may stabilize base-pairing between miRNAs and their target genes. Together, our study provides a comprehensive landscape of miRNA NTAs in human biofluids, which paves way for further biomarker discoveries. The insights generated in our work built a foundation for future functional, mechanistic and translational discoveries.

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There is no magic bullet: the importance of testing reference gene stability in RT-qPCR experiments across multiple closely related species

PeerJ ◽

10.7717/peerj.9618 ◽

2020 ◽

Vol 8 ◽

pp. e9618

Author(s):

Bert Foquet ◽

Hojun Song

Keyword(s):

Gene Expression ◽

Related Species ◽

Reference Genes ◽

Target Genes ◽

Quantitative Polymerase Chain Reaction ◽

Magic Bullet ◽

Experimental Conditions ◽

Closely Related Species ◽

Expression Levels ◽

Gene Stability

Reverse Transcriptase quantitative Polymerase Chain Reaction (RT-qPCR) is the current gold standard tool for the study of gene expression. This technique is highly dependent on the validation of reference genes, which exhibit stable expression levels among experimental conditions. Often, reference genes are assumed to be stable a priori without a rigorous test of gene stability. However, such an oversight can easily lead to misinterpreting expression levels of target genes if the references genes are in fact not stable across experimental conditions. Even though most gene expression studies focus on just one species, comparative studies of gene expression among closely related species can be very informative from an evolutionary perspective. In our study, we have attempted to find stable reference genes for four closely related species of grasshoppers (Orthoptera: Acrididae) that together exhibit a spectrum of density-dependent phenotypic plasticity. Gene stability was assessed for eight reference genes in two tissues, two experimental conditions and all four species. We observed clear differences in the stability ranking of these reference genes, both between tissues and between species. Additionally, the choice of reference genes clearly influenced the results of a gene expression experiment. We offer suggestions for the use of reference genes in further studies using these four species, which should be taken as a cautionary tale for future studies involving RT-qPCR in a comparative framework.

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Selection and Validation of Reference Genes for the qRT-PCR Assays of Populus ussuriensis Gene Expression under Abiotic Stresses and Related ABA Treatment

Forests ◽

10.3390/f11040476 ◽

2020 ◽

Vol 11 (4) ◽

pp. 476

Author(s):

Ming Wei ◽

Yingxi Chen ◽

Mengqiu Zhang ◽

Jingli Yang ◽

Han Lu ◽

...

Keyword(s):

Gene Expression ◽

Cold Stress ◽

Internal Control ◽

Reference Genes ◽

Target Genes ◽

High Salinity ◽

High Yield ◽

Pcr Analysis ◽

Qrt Pcr ◽

Populus Ussuriensis

Populus ussuriensis Kom. is one of the most important tree species for forest renewal in the eastern mountainous areas of Northeast China due to its fast growth, high yield, and significant commercial and ecological value. The selection of optimal reference genes for the normalization of qRT-PCR data is essential for the analysis of relative gene expression. In this study, fourteen genes were selected and assessed for their expression stability during abiotic stress (drought, high salinity, and cold stress) and after the treatment with the drought-related hormone ABA. Three algorithms were used, geNorm, NormFinder, and BestKeeper, and a comprehensive ranking of candidate reference genes was produced based on their output. The most appropriate reference genes were UBQ10 and RPL24 for drought and ABA treatment, UBQ10 and TUB3 for cold stress, and UBQ10 and 60S rRNA for high salinity. Overall, UBQ10 was the most stable reference gene for use as an internal control, whereas PP2A was the least stable. The expression of two target genes (P5CS2 and GI) was used to further verify that the selected reference genes were suitable for gene expression normalization. This work comprehensively assesses the stability of reference genes in Populus ussuriensis and identifies suitable reference genes for normalization during qRT-PCR analysis.

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